为什么set.seed()影响R中的sample() [英] Why set.seed() affect sample() in R

问题描述

我一直认为set.seed()仅使随机变量生成器(例如rnorm)为任何特定的一组输入值生成唯一的序列.

I always thought set.seed() only makes random variable generators (e.g., rnorm) to generate a unique sequence for any specific set of input values.

但是，我想知道为什么当我们设置set.seed()时，功能sample()不能正确执行其工作?

However, I'm wondering, why when we set the set.seed(), then the function sample() doesn't do its job correctly?

具体地说，给出以下示例，有一种方法可以在rnorm之前使用set.seed，但是如果sample仍会从该rnorm中产生新的随机样本>多次运行?

Specifically, given the below example, is there a way I can use set.seed before the rnorm but sample would still produce new random samples from this rnorm if sample is run multiple times?

set.seed(123458)
x.y = rnorm(1e2)

sampled = sample(x = x.y, size = 20, replace = TRUE)

plot(sampled)

推荐答案

根据?set.seed

"如果使用seed = NULL进行调用，它将重新初始化(请参见注意")，就像没有 种子尚未确定."

"If called with seed = NULL it re-initializes (see ‘Note’) as if no seed had yet been set."

因此，由于rnorm和sample都受set.seed()的影响，因此您可以执行以下操作:

So, since rnorm and sample are both affected by set.seed(), you can do:

set.seed(639245)
rn <- rnorm(1e2)
set.seed(NULL)
sample(rn,5)

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